Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

Optimization methods applied to renewable and sustainable energy: A review

The paper reviews different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power. We consider both supply and demand side measures. In addition to presenting energy system flexibility measures, their importance to renewable electricity is discussed. The flexibility measures available range from traditional ones such as grid extension or pumped hydro storage to more advanced strategies such as demand side management and demand side linked approaches, e.g. the use of electric vehicles for storing excess electricity, but also providing grid support services. Advanced batteries may offer new solutions in the future, though the high costs associated with batteries may restrict their use to smaller scale applications. Different “P2Y”-type of strategies, where P stands for surplus renewable power and Y for the energy form or energy service to which this excess in converted to, e.g. thermal energy, hydrogen, gas or mobility are receiving much attention as potential flexibility solutions, making use of the energy system as a whole. To “functionalize” or to assess the value of the various energy system flexibility measures, these need often be put into an electricity/energy market or utility service context. Summarizing, the outlook for managing large amounts of RE power in terms of options available seems to be promising.

https://research.aalto.fi/files/6557604/lund_et_al_review.pdf

Review of energy system flexibility measures to enable high levels of variable renewable electricity

Artificial intelligence techniques for photovoltaic applications: A review

Hybrid energy systems are being utilized for supplying electrical energy in urban, rural and remote areas to overcome the intermittence of solar and wind resources. A hybrid renewable energy system incorporates two or more electricity generation options based on renewable energy or fossil fuel unit. The techno-economic analysis of the hybrid system is essential for the efficient utilization of renewable energy resources. Due to multiple generation systems, hybrid system analysis, is quite complex and requires to be analyzed thoroughly. This requires software tools for the design, analysis, optimization, and economic viability of the systems. In this paper, 19 softwares with their main features and current status are presented. The softwares studied are HOMER, Hybrid2, RETScreen, iHOGA, INSEL, TRNSYS, iGRHYSO, HYBRIDS, RAPSIM, SOMES, SOLSTOR, HySim, HybSim, IPSYS, HySys, Dymola/Modelica, ARES, SOLSIM, and HYBRID DESIGNER. The research work related to hybrid systems carried out using these softwares at different locations worldwide is also reviewed. The main objective of the paper is to provide the current status of these softwares to provide basic insight for a researcher to identify and utilize suitable tool for research and development studies of hybrid systems. The capabilities of different softwares are also highlighted. The limitations, availability and areas of further research have also been identified.

Review of software tools for hybrid renewable energy systems

Public awareness of the need to reduce global warming and the significant increase in the prices of conventional energy sources have encouraged many countries to provide new energy policies that promote the renewable energy applications. Such renewable energy sources like wind, solar, hydro based energies, etc. are environment friendly and have potential to be more widely used. Combining these renewable energy sources with back-up units to form a hybrid system can provide a more economic, environment friendly and reliable supply of electricity in all load demand conditions compared to single-use of such systems. One of the most important issues in this type of hybrid system is to optimally size the hybrid system components as sufficient enough to meet all load requirements with possible minimum investment and operating costs. There are many studies about the optimization and sizing of hybrid renewable energy systems since the recent popular utilization of renewable energy sources. In this concept, this paper provides a detailed analysis of such optimum sizing approaches in the literature that can make significant contributions to wider renewable energy penetration by enhancing the system applicability in terms of economy.

Optimum design of hybrid renewable energy systems: Overview of different approaches

Optimised model for community-based hybrid energy system

Peak-load management in steel plants

Electrolytic process, employed for manufacturing basic chemicals like caustic soda and chlorine, is highly energy intensive. Due to escalating costs of fossil fuels and capacity addition, the electricity cost has been increasing for the last few decades. Electricity intensive industries find it very difficult to cope up with higher electricity charges particularly with time-of-use (TOU) tariffs implemented by the utilities with the objective of flattening the load curve. Load management programs focusing on reduced electricity use at the time of utility's peak demand, by strategic load shifting, is a viable option for industries to reduce their electricity cost. This paper presents an optimization model and formulation for load management for electrolytic process industries. The formulation utilizes mixed integer nonlinear programming (MINLP) technique for minimizing the electricity cost and reducing the peak demand, by rescheduling the loads, satisfying the industry constraints. The case study of a typical caustic-chlorine plant shows that a reduction of about 19% in the peak demand with a corresponding saving of about 3.9% in the electricity cost is possible with the optimal load scheduling under TOU tariff.

Peak Load Management in Electrolytic Process Industries

In this article, a hybrid energy system consisting of biomass, wind, solar photovoltaic (SPV), and battery is proposed. The sources are operated to deliver energy at optimum efficiency. An optimization model is developed to supply the available energy to the loads according to the priority. It is also proposed to maintain a fair level of energy storage to meet the peak load demand together with biomass, wind, and solar photovoltaic during low or no solar radiation periods or during low wind periodsA case study was completed using load data collected from three villages (300 km south of Chennai, India). Simulations carried out for a one-year period proved the effectiveness of the developed energy management system by satisfying the load demand, nonlinear seasonal variations, and equipment constraints. Also with the proposed energy management, it is found that the load demand is almost satisfied, there is less dumped energy, and the state of charge of the battery is at a reasonably good level. Economic anal...

Optimal Operation of Biomass/Wind/PV Hybrid Energy System for Rural Areas

This paper presents a generalized formulation to determine the optimal operating strategy of industrial cogeneration schemes. The model includes both electrical and thermal systems. All types of cogeneration equipment viz steam turbines, gas turbines, diesel generators, steam boilers, waste heat recovery boilers, and steam header configuration, with grid connection are separately represented in terms of their characteristics so that the model has the flexibility to be applicable for any industry. The model is multiperiod and nonlinear in nature and utilizes a Newton based algorithm for minimizing the total operating cost. Optimal operating strategies for different equipment combinations for a typical industrial configuration under different electricity tariff rates are determined using the proposed model. The results show that industrial cogeneration has a significant potential in reducing peak coincident demand. The optimal response of cogeneration plant reduces the peak coincident demand by 42.8 MW (71%) under flat tariff and 54 MW (90%) under TOU tariff. The industry gets 16% saving in the total operating cost with the optimal operation of the cogeneration plant. When power export is permitted to grid, it provides the utility a peak saving of 63.7 MW.

S. Ashok

Papers

Optimised model for community-based hybrid energy system

Peak-load management in steel plants

Peak Load Management in Electrolytic Process Industries

Optimal Operation of Biomass/Wind/PV Hybrid Energy System for Rural Areas

Optimal operation of industrial cogeneration for load management